An image processing method for estimating the motion of objects in a sequence of noisy images is already known from the publication "ROBUST BLOCK-MATCHING MOTION-ESTIMATION TECHNIQUE FOR NOISY SOURCES" by ROBERT M. ARMITANO et al. in "1997 IEEE, International Conference on Acoustics, Speech and Signal Processing", Vol. IV, pp. 2685-2688.
In order to carry out the method described in the cited publication, a sequence of images is acquired until an instant t. The image treated at the instant t is the last image arriving. It is divided into adjoining blocks which are denoted by their co-ordinates; a current block from among said blocks is examined. A block having the same co-ordinates is determined in the preceding image, occurring at the instant t-1, and a search window whose dimensions are linked to the presumed amplitude of the motion is formed around this block. This method, being based on a so-called Block Matching Algorithm (B.M.A.), aims to determine, in the search window, a so-called matching block which matches the current block and is that block which, in conformity with a predetermined intensity similarity criterion, has luminosity properties which are nearest to those of the current block. The determination of the matching block yields a motion vector which measures the spatial translation between the current block in the image at the instant t and the matching block in the preceding image of the instant t-1.
This motion estimation method includes an estimation of a coarse motion vector in order to provide an approximate location of the matching block, followed by the application of an intensity similarity criterion in order to estimate a real motion vector around the coarse motion vector. The similarity criterion is not described.
The estimation of the coarse motion vector includes the determination of a plurality of p motion vectors relating to matching blocks situated in respective ones of an identical number of p successive temporal images which precede the image which is processed at the instant t and contains the current block, and a linear temporal filtering operation which yields said coarse motion vector as a weighted mean value of p preceding motion vectors. Such linear temporal filtering of p preceding motion vectors is of the predictive type, which means that, p preceding motion vectors relating to p matching blocks in the preceding images being known, the coarse motion vector between the instants t and t-1 is predicted on the basis of a specific hypothesis that the motion estimated over the p preceding, successive matching blocks is strictly linear and continuous. The similarity criterion is then locally applied around the coarse vector in order to estimate the real motion vector.
Because of the fact that the above method implies such a prediction step, it loses its effectiveness whenever a new motion appears, because in that case the coarse motion vector cannot be determined since the p preceding motion vectors do not exist. Therefore, the real vector, based on the coarse vector, can no longer be found locally.